Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Distance Problem

Distance Problem

When an object's velocity changes over time, the total distance traveled can be determined by summing small displacement intervals over short increments. This approach approximates the true distance through numerical summation and the use of integral calculus. An estimate of the total displacement can be obtained by measuring velocity at regular intervals and multiplying each value by the corresponding time step.If a runner accelerates over the first three seconds of a race, speed measurements...

Mean Absolute Deviation

Mean Absolute Deviation

The mean absolute deviation is also a measure of the variability of data in a sample. It is the absolute value of the average difference between the data values and the mean.
Let us consider a dataset containing the number of unsold cupcakes in five shops: 10, 15, 8, 7, and 10. Initially, calculate the sample mean. Then calculate the deviation, or the difference, between each data value and the mean. Next, the absolute values of these deviations are added and divided by the sample size to...

Routh-Hurwitz Criterion II

Routh-Hurwitz Criterion II

In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...

Wilcoxon Signed-Ranks Test for Median of Single Population

Wilcoxon Signed-Ranks Test for Median of Single Population

The Wilcoxon signed-rank test for the median of a single population is a nonparametric test used to evaluate whether the median of a population differs from a specified value. Unlike parametric tests, it does not require data to follow a normal distribution, making it suitable for non-normal or small samples. The test begins by calculating the difference (d) between each observation and the hypothesized median. The absolute values of these differences are ranked in ascending order, with ties...

Routh-Hurwitz Criterion I

Routh-Hurwitz Criterion I

Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...

Weighted Mean

Weighted Mean

While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Effect of renin-angiotensin system inhibitors on pemetrexed plus platinum-induced hematological toxicities: a multicenter retrospective study using three propensity score analyses.

Die Pharmazie·2021

Same author

Journal of Artificial Organs 2019: the year in review : Journal of Artificial Organs Editorial Committee.

Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs·2020

Same author

Journal of Artificial Organs 2018: the year in review : Journal of Artificial Organs Editorial Committee.

Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs·2019

Same author

Successful Steroid Therapy for Lipoid Pneumonia Developing After Allogeneic Hematopoietic Stem Cell Transplant: A Case Report.

Transplantation proceedings·2018

Same author

Journal of Artificial Organs 2017: the year in review : Journal of Artificial Organs Editorial Committee.

Journal of artificial organs : the official journal of the Japanese Society for Artificial Organs·2018

Same author

12-OH-17,18-Epoxyeicosatetraenoic acid alleviates eosinophilic airway inflammation in murine lungs.

Allergy·2017

Search research articles

Related Experiment Video

Updated: May 29, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

An optimal global nearest neighbor metric.

K Fukunaga¹, T E Flick

¹School of Electrical Engineering, Purdue University, West Lafayette, IN 47907.

IEEE Transactions on Pattern Analysis and Machine Intelligence

|August 27, 2011

Summary

A new quadratic metric minimizes mean-squared error for nearest neighbor classification. This metric outperforms the Euclidean metric, offering improved accuracy in statistical analysis.

Area of Science:

Statistics
Machine Learning
Pattern Recognition

Background:

Nearest neighbor (NN) classification is a fundamental algorithm in pattern recognition.
The performance of NN methods can be sensitive to the choice of distance metric.
Minimizing the difference between asymptotic and finite sample risks is crucial for robust classification.

Purpose of the Study:

To propose a novel quadratic distance metric, dAO(X, Y), designed to minimize mean-squared error.
To compare the proposed metric's performance against the standard Euclidean metric.
To develop a nonparametric method for estimating the metric's parameters (Ao).

Main Methods:

Definition of a quadratic metric: dAO(X, Y) = [(X - Y)T AO(X - Y)]^0.5.
Heuristic argument under linearity assumptions to demonstrate lower mean-squared error compared to Euclidean distance.

Related Experiment Videos

Last Updated: May 29, 2026

Modeling the Functional Network for Spatial Navigation in the Human Brain

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

Development of a nonparametric estimation technique for the matrix Ao.

Main Results:

The proposed quadratic metric dAO potentially yields lower mean-squared error than the Euclidean metric.
A nonparametric method for estimating Ao is successfully developed.
An alternative parametric distance measure is suggested for Gaussian mixture distributions in localized regions.

Conclusions:

The novel quadratic metric offers a promising approach to enhance nearest neighbor classification accuracy.
The nonparametric estimation of Ao provides a practical way to implement the proposed metric.
The study highlights the importance of metric selection in statistical pattern recognition, especially for mixture models.